The central purpose of this project is to develop to the scientific community thousands of rat ESTs and a high density radiation hybrid map consisting of at least 10,000 unique rat ESTs. These 10,000 mapped ESTs will be chosen from a non-redundant set consisting of 30,000 ESTs representing transcripts from a variety of adult tissues and whole embryos from different stages of development. The EST map will be anchored to the evolving rat genetic map. An aggressive strategy based on subtractive hybridizations of very complex normalized libraries will be applied to minimize the redundant identification of ESTs at all times, while enhancing significantly the representation of the (otherwise) rare transcripts (not as likely to be sampled in more random approaches) in our final collections of ESTs. All clones from which ESTs will be generated will be arrayed and made available to the research community. Both 5' and 3' ESTs will be generated for each of the 30,000 arrayed clones of the rat non- redundant set. Normalized libraries enriched for rat full-length cDNA will be constructed which will be useful for screening to obtain longer full-length clones of all available rat ESTs, including those generated by other investigators. In addition, a hybrid selected-library of full- length or near full-length representatives of the (truncated) clones of the non-redundant set will be constructed and 15,000 3' ESTs (total of 20,000 attempts) will be generated to establish the links between clones of the non-redundant set and clones of the full-length sub- library. Both the complete library and the hybrid selected sub-library of full-length cDNAs will be arrayed and made available. Cost- effective distribution of all resources including EST primers, clones from which the ESTs were generated, and reagents for full-length clone screening will occur through an established collaboration with the private sector. Finally, public access to ESTs, sequences and map information will be provided. A state of the art information management system will track and archive all data, resources and outcomes. The research strategy takes advantage of a novel yet fully tested approach, named Serial Subtraction of Normalized Libraries (SSNL), designed to ensure that sequencing effort is efficient in identifying novel transcripts (identification of the highest possible number of unique clones with a limited amount of sequencing.